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Freelance Computational Biology Postdoc information

What is the difference between Freelance Computational Biology Postdoc vs Research Scientist in Computational Biology?

AspectFreelance Computational Biology PostdocResearch Scientist in Computational Biology
CredentialsTypically PhD in computational biology or related fieldPhD often required; sometimes with postdoctoral experience
Work EnvironmentIndependent, project-based, often remote or contract workInstitutional or corporate labs, full-time employment
Employer & IndustryFreelance clients, biotech startups, academiaUniversities, research institutes, biotech companies
Work FocusProject-specific, flexible, consulting or research collaborationsLong-term research projects, product development, team collaboration

The main difference is that a Freelance Computational Biology Postdoc works independently on short-term projects, often remotely, while a Research Scientist in Computational Biology is typically a full-time employee in an institution or company, focusing on ongoing research and development within a team.

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Postdoctoral AI Researcher in AI/ML for Cellular and Protein Computational Biology

Harvard University

Cambridge, MA • On-site

Full-time

Re-posted 17 days ago

Harvard University rating

8.5

Company rating: 8.5 out of 10

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Job description

Position
Details
Title
Postdoctoral AI Researcher in AI/ML for Cellular and Protein Computational Biology
School
Faculty of Arts and Sciences
Department/Area
Kempner Institute at Harvard University
Position Description
The Kempner Institute at Harvard University seeks early-career researchers to help shape the future of AI as Postdoctoral AI Researchers. We are looking for candidates with deep expertise in modern AI/ML and a strong record of research accomplishment who are excited to develop new AI approaches for high-impact problems in cellular and protein computational biology.
This role focuses on applying modern AI/ML methods to protein and cellular biology, including protein structure prediction, protein-protein and small-molecule-protein docking, cell state prediction from large-scale Perturb-seq datasets, and multimodal modeling of protein function and cellular state.
We seek candidates with strong technical preparation in modern AI/ML, a demonstrated record of scholarly achievement, and experience in computational biology or biological data analysis. Strong candidates may come from protein-focused, cell-state-focused, or multimodal biological modeling backgrounds and will have expertise in one or more of the following areas:
  • foundation model training, evaluation, and adaptation
  • protein structure modeling and docking
  • cell state prediction from large-scale perturbation datasets
  • multimodal modeling for protein function and cellular state prediction
  • familiarity with AlphaFold, RFDiffusion, CellCap, or related models for protein and cellular biology

Postdoctoral AI Researchers will work closely with Kempner faculty, researchers, and students on foundational machine learning and biologically informed scientific applications. The position is particularly well-suited to candidates eager to apply their technical expertise in modern AI to important problems in protein biology, cellular systems, and biological intelligence, while continuing to grow as scholars within a collaborative academic environment.
Candidates should be within 2 years of receiving their doctoral degree and will work under the direction of Kempner Institute faculty.
Appointment Terms
  • Postdoctoral AI Researchers conduct research under the general supervision of one or more Harvard faculty members.
  • The appointment is for one year; reappointment may be possible for up to a total of three years, contingent on funding, project needs, satisfactory performance, and mutual interest.
  • This is a full-time, benefits-eligible postdoctoral appointment based at the Kempner Institute at Harvard University.
  • Due to the importance of in-person mentoring and collaboration, this position is based on campus, full-time, at Harvard University. Remote work for this position is not possible.

Basic Qualifications
  • PhD in computer science, statistics, electrical engineering, applied mathematics, computational biology, bioengineering, biophysics, or a related quantitative field required by the expected start date.
  • Candidates must have received their PhD on or after September 15, 2024, or be on track to complete all PhD requirements by the expected start date of October 15, 2026.
  • Demonstrated expertise in modern AI/ML, including deep learning and hands-on experience with frameworks such as PyTorch or JAX.
  • Strong publication record in leading venues such as ICML, ICLR, NeurIPS, RECOMB, ISMB, or comparable conferences and journals, and/or substantial open-source research contributions.
  • Demonstrated experience implementing, training, evaluating, or fine-tuning modern machine learning models.
  • Strong programming skills in Python and experience building and maintaining research code.
  • Demonstrated ability to use modern AI-assisted and agentic coding tools effectively, such as Claude Code, Codex, or similar systems, in research and development workflows.
  • Experience in computational biology, biological data analysis, protein modeling, cellular modeling, or related areas.
  • Ability to work effectively in a collaborative research environment and communicate technical work clearly.

Additional Qualifications
  • Experience with foundation model training, post-training, adaptation, or evaluation.
  • Experience with protein structure modeling, protein-protein docking, or small-molecule-protein docking.
  • Experience with cell state modeling from large-scale perturbation datasets, including Perturb-seq or related data.
  • Experience with multimodal modeling for protein function or cellular state prediction.
  • Familiarity with models and methods relevant to protein and cellular biology, including AlphaFold, RFDiffusion, CellCap, or related systems.
  • Experience with large-scale datasets, distributed training, or high-performance computing environments.
  • Expertise in scientific applications of AI/ML in protein biology, cellular systems, and related areas of computational biology.

Special Instructions
Please submit the following items in PDF format no later than 11:59pm EST Monday, June 8, 2026:
  • CV
  • A research statement of no more than 2 pages describing your experience using modern AI/ML for protein structure, cellular state, or related biological modeling problems. Please be specific about your individual contributions.
  • References - 2-3 required
    • Please give the emails of up to 3 individuals who can describe your previous related work.
    • Referees will be contacted to submit the letters directly to the Kempner Institute.
    • The application will not be considered complete until all letters have been received.

Candidates selected for further consideration will be asked to submit a short video presentation reviewing their past work; additional details will be provided at that stage. Following review of the videos, a subset of candidates will be invited to interview with members of the selection committee via Zoom.
Applications received after the deadline will be reviewed on a rolling basis if positions remain available.
We anticipate a start date of October 15, 2026.
Contact Information
Molly Marshall
Contact Email
KempnerInstitute@Harvard.edu
Salary Range
Expected salary is $100,000, subject to compliance with the applicable salary requirements for the appointment. This is a benefits eligible position.
Minimum Number of References Required
2
Maximum Number of References Allowed
3
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